International Journal of Science, Engineering and TechnologyAuthors: Lobzang Tobgye
Abstract: Digital Elevation Models (DEMs) are essential geospatial datasets representing Earth's surface elevation, widely used in applications such as flood modeling, urban planning, and disaster response. However, DEMs derived from sources like satellite imagery, LiDAR, or photogrammetry can contain errors due to sensor limitations, processing issues, and surface conditions. Accurate validation against high-quality reference data, such as ground-based surveys or GPS measurements, is crucial, employing statistical metrics like Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Standard Deviation of Errors (STD) to quantify discrepancies. This study assesses the vertical accuracy of a local 10 m DEM (TopoDEM) generated from contour lines and spot heights derived from 1:25,000 digital topographic maps via digital photogrammetry, compared to the Cartosat-1 DEM (CartoDEM) by ISRO, which claims 8 m accuracy at LE90. Validation utilized ground control points (GCPs) across test areas in Bhutan (Gelephu, Paro, and Trashiyangtse), computing elevation differences and statistical measures. Results indicate TopoDEM generally outperforms CartoDEM, with RMSE values ranging from 4.56 m to 6.62 m across terrains, versus CartoDEM's 4.26 m to 9.04 m. TopoDEM showed lower errors in Paro and Trashiyangtse, while Gelephu exhibited higher residuals due to recent topographic changes. Over flat terrains like Gelephu, RMSE was 4.26–6.62 m, and in high-altitude areas like Trashiyangtse, it ranged from 6.42–9.04 m. In conclusion, TopoDEM demonstrates superior vertical accuracy, underscoring the value of high-resolution datasets from digital photogrammetry for reliable elevation modeling in diverse landscapes. This highlights the need for rigorous accuracy assessments to ensure DEM reliability in critical applications.
